Personalized Interactive Network with Knowledge Management System

ABSTRACT

Systems and methods are disclosed for personalizing interaction between an information/service/product provider using a knowledge management (KM) system that tracks data exchanged between users and the provider over multiple communication channels. User requests to an information/service/product provider can made via multiple different channels, such as by using ATMs, PDAs, cell phones, computers accessing web sites or other Web Devices, Voice Response Units (VRUs), and others. User requests submitted over these multiple channels are routed into an integrated KM system that services these requests. The user requests are serviced in such a manner that they are personalized in multiple aspects to enrich the user&#39;s experience.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.13/326,271, filed Dec. 14, 2011, which in turn is a continuation of U.S.patent application Ser. No. 11/950,112, filed Dec. 4, 2007, which inturn is a continuation of U.S. patent application Ser. No. 09/564,783,filed May 4, 2000, now U.S. Pat. No. 7,370,004, which in turn claims thebenefit of and incorporates by reference the subject matter of U.S.Provisional Application Ser. No. 60/165,739, filed Nov. 15, 1999. Eachof U.S. patent application Ser. No. 13/327,271, U.S. patent applicationSer. No. 11/950,112, U.S. patent application Ser. No. 09/564,783 andU.S. Provisional Application Ser. No. 60/165,739 is hereby incorporatedby reference in its entirety.

BACKGROUND OF THE INVENTION

The present invention relates to a system for personalized interactionover a communications channel between a user and a provider ofinformation/services/goods. In particular, the present invention allowsfor personalized interactivity between an Internet web site user and theweb site provider of information/services/goods. For example, thepresent invention allows a provider of services, for example, a providerof financial services such as a bank, to interact personally through acustomer personalized website with a customer of that financial serviceprovider. Although the invention may be used to personalize theprovision of financial services over a communications channel, it is notlimited to financial services but can be used to personalize theinteraction between a customer and a provider of any products, goods,services and/or information of any kind In particular, the presentinvention allows the provider of the information/goods/services topersonalize the web site to the preferences of the particular user, forexample, preferences such as interests, hobbies, business interests,product/service preferences, etc. Although an example has just beenprovided of a personalized approach to providing an Internet basedservice, the invention is equally applicable to any other communicationschannel including such channels involving interaction through automaticteller machines (ATMs) and other communications devices and kiosks,other communication channels, intranets or extranets, e-mail, telephonecommunications, faxes, call centers, branch offices, etc.

There are some limited forms of personalized interactive systemspresently in operation, in particular, over the Internet. For example,Amazon.com provides a service which can select books for customers basedupon their previous selections and preferences. However, these systemsare limited in scope, and basically only use what is known ascollaborative filtering to infer either what should be offered next orto make recommendations to the user.

Another system patented by Broadvision, described in U.S. Pat. No.5,710,887, provides for electronic commerce over a computer drivennetwork. An aim of this system is to allow commerce to be conductedacross a number of different platforms and networks. Although offeringthe ability to be implemented over different networks, not just theinternet, this system offers limited ability to customize theinteraction between the customer and the provider of goods/services sothat each customer interacts in a unique way with the provider based onthe customer's preference, characteristics, lifestyle, etc. TheBroadvision patent creates a participant program object that identifiesthe participant and contains information about the participant, e.g.,name, address, privacy controls, demographic data and payment methods.However, the system is not capable of making knowledge driven decisionsabout a customer to personalize the interaction with the provider sothat it takes into account more intangible customer characteristics suchas preferences, lifestyles, and such customer characteristics as, forexample, preferred tone of voice of interaction, decisions about userinterests and hobbies, etc., that may be important to making anelectronic interaction more “human” or personal.

Another system is described in U.S. Pat. No. 6,014,638. assigned toAmerica Online, Inc. This system, however, is directed to an Internetonly based system and is not applicable to a system which is adaptableto multiple channels and points of contact. Further, the system of theAOL patent does not allow for personalization in real time, i.e., usingcurrent interactions with the user.

BRIEF SUMMARY OF THE INVENTION

The present invention aims to manage knowledge obtained from customerinteractions and personalize the information/product/services that areoffered to the customer as a result of those interactions. The presentinvention utilizes data obtained from past and present interactions tomake decisions about what to offer the customer and about whatinformation/products/services the customer may be interested in.Further, the present invention is directed at totally personalizing therelationship between the customer and the information/service/productprovider based upon using all the knowledge which can be obtained frompast and present interactions with the customer to personalize therelationship with the customer. In the context of an Internet web site,the present invention personalizes the web site to the customer'spreferences, characteristics and interests, etc. and pushes information,products, etc. that would be suitable to the customer.

The present invention provides a single, integral system that allows allchannels to utilize the system, thus centralizing knowledge and creatinga unique customer interaction experience.

Further, the present invention meets a need to integrate within aninformation/product/service provider, the various departments of theinformation/product/service provider so that the variousinformation/product/service providers within a single company, forexample, or even amongst groups of companies, can provide a plurality ofinformation/services/products to the customer using an integrated or“cross channel” approach. For example, taking the example of a financialservice provider, the present invention allows information concerning anATM user having a high savings balance to be known to an investmentdepartment of the financial service provider so that the financialservice provider can provide investment opportunities to that customer.Taking another example, a financial service customer having a highsavings balance may be offered information concerning real estatemortgage offerings or loans on the rationale that a customer with a highbalance may be saving funds to purchase and/or finance a home. In thisway, the system of the invention allows collaboration andcross-fertilization (cross-application) across different channels of aninformation/service/product provider.

Presently, in many institutions that provide multipleservices/products/information, one department providing a particularservice/product/information may be totally unaware of prospects known toanother department specializing in a different area of that same companyor of knowledge that a customer exists in other relationships. Thepresent invention, through an integrated system, will allow the companyto be more responsive to the customer's various needs. In effect, thepresent invention has the effect of ending what is often called the“silo” mentality, i.e., the compartmentalizing of branches ordepartments in a company so that one branch or department is unaware ofprospects/customers from another branch or department. A customer oruser is defined as anyone who uses the system. The present inventionaims to achieve the above objects by integrating various channelsthrough which customers communicate with the information/service/productprovider. The various channels may include the Internet, but also otherchannels such as phone lines, automatic teller machines, branch offices,bank cards, e-mail, direct mail and most other channels ofcommunication. Further, the system of the invention allows use ofmultiple channels, e.g., a user may initiate communication using an ATM,but receive a response over the internet or fax or by phone or e-mail.The system allows the customer and provider to interact and allowscustomer to customer interaction or user to user interaction within aproduct/service information provider.

According to the invention, the above described objects are achieved bya system for personalizing interaction between a user communicating overat least one communication channel and a provider ofinformation/products/services, the user having a communication devicefor communication over the channel with the provider, the systemcomprising: a channel interface for interfacing with the channel; aproduct/service interface for interfacing with aninformation/product/service provider; and a knowledge management systemcoupled to the channel and product/service interfaces, the knowledgemanagement system comprising a knowledge/management repository storinginformation concerning the user, the information obtained frominteraction with the user over the channel including currentinteractions between the user and the knowledge management system andfurther for storing information concerning a plurality ofinformation/products/services to offer to the user; and apersonalization engine for making a decision as to which of theplurality of information/product/services to present to the user overthe communication channel based on the stored information in theknowledge/management repository.

According to one aspect, the system of the invention comprises aplurality of managers, brokers and services that contain and utilizedatabases and objects.

According to another aspect, the invention comprises a method forpersonalizing interaction between a user communicating over at least onecommunication channel and a provider of information/products/services,the user having a communication device for communication over thechannel with the provider with which the user interfaces with thechannel. A knowledge management system is interfaced with the channeland an information/product/service provider. Information is stored in aknowledge management repository concerning the user, the informationobtained from interaction with the user over the channel includingcurrent interactions between the user and the knowledge managementsystem. Further, information is stored in the knowledge managementrepository concerning a plurality of information/products/services tooffer to the user. A decision is made as to which of the plurality ofinformation/products/services to present to the user over thecommunication channel based on the stored information in the knowledgemanagement repository.

According to yet another aspect, the present invention provides a systemfor personalizing interaction between a user communicating over at leastone communication channel and a provider ofinformation/products/services, the user having a communication devicefor communication over the channel with the provider, the systemcomprising: a channel interface for interfacing with the channel; aproduct/service interface for interfacing with aninformation/product/service provider; and a knowledge management systemcoupled to the channel and product/service interfaces. The knowledgemanagement system comprises a knowledge management repository storinginformation concerning the user, the information obtained from at leastone of interaction with the user over the channel including currentinteractions between the user and the knowledge management system; andinformation obtained about the user from other sources. The knowledgemanagement repository further storing information concerning a pluralityof information/products/services to offer to the user; and apersonalization engine for making a decision as to which of theplurality of information/product/services to present to the user and forpersonalizing content of the information/product/services provided tothe user over the communication channel based on the stored informationin the knowledge management repository.

According to still yet another aspect, the invention provides a methodfor personalizing interaction between a user communicating over at leastone communication channel and a provider ofinformation/products/services, the user having a communication devicefor communication over the channel with the provider in which the useris interfaced with the channel. A knowledge management system isinterfaced with the channel and an information/product/service provider.Information is stored in a knowledge management repository concerningthe user, the information obtained from at least one of interaction withthe user over the channel including current interactions between theuser and the knowledge management system and information obtained fromother sources. Information is further stored in the knowledge managementrepository concerning a plurality of information/products/services tooffer to the user. A decision is made as to which of the plurality ofinformation/product/services to present to the user and forpersonalizing content of the information/product/services provided tothe user over the communication channel based on the stored informationin the knowledge management repository.

The system of the invention accordingly provides a framework ofcomponents, their relationships, functions, and purposes for creatingand maintaining a personalized interaction that is constant and can betailored to any communications channel.

Further, the system of the invention can be used with any interactivecommunication channel and further is applicable to a wide variety ofgoods/products/services/information including, without limitation,financial products/services, legal products/services, entertainmentproducts/services, government products/services, personalproducts/services, corporate products/services, consumer/individualproducts/services and information in general. For example, with respectto financial institutions, information such as payment information,statements, documents and files can be stored. Personalized offeringscan be provided to the customer in such areas as archives for legalrequirements, product fulfillment and customer service. For law firms,document storage can be provided and the interaction personalized. Forexample, archives for legal requirements or data mining of intellectualproperty are some examples of personalized offerings which can beprovided by the system of the invention. With respect to entertainmentcompanies, media such as music and video libraries may be stored.Personalized offerings such as consumer sales/global order fulfillmentand video and audio screening may be provided. For governmentalagencies, forms, deeds, statements and other documents and files etc.may be stored and personalized offerings may be provided with respect tothese, for example, personalized data views can be provided. The systemof the invention provides convenience, security and efficiency. Withrespect to personal services and markets, examples of media storedinclude PC backup, documents, music and video data, which can be usedfor internal use, customer service or order fulfillment, for example.Corporations can use the invention for documents/file storage, tradematerials and/or vault services, for example. These can be used forinternal use work flow improvement or order fulfillment.

Other features and advantages of the present invention will becomeapparent from the following detailed description of the invention whichrefers to the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will be described in greater detail in the followingdetailed description with reference to the accompanying drawings inwhich:

FIG. 1 shows the overall framework for the personalization architectureof the present invention;

FIG. 1A is a linear technical architecture diagram showing the variouslayers of the system of the invention and their applicability to variousinput channels and products and/or services, their relationships andinteractions; this drawing uses time with zero minutes being thedistribution channel with 1+ being the product layer;

FIG. 1B shows an example of operation of the system illustrating a casestudy demonstrating the components involved;

FIG. 1C shows modeling of the data using, for example, the “Papaa”framework (to be described herein);

FIG. 2 is a more detailed block diagram of the basic components of thepersonalization architecture including the distribution channels andproduct processors;

FIG. 3 is a yet more detailed block diagram of the personalizationarchitecture of the invention, including components, relationships andflows;

FIGS. 4, 5, 5A, 6 and 7 are flow charts and accompanying related dataapplicable to users using a web site which has been personalized andshowing the techniques used to personalize the experience and flow;

FIGS. 8 and 8A are detailed block diagrams of the interaction of thepersonalization manager component shown in FIGS. 2 and 3, this flowdemonstrating the role and functionality of this component;

FIG. 8A shows the technical objects used to construct thepersonalization manager;

FIGS. 9 and 9A are block diagrams showing the interaction of componentsof the invention based upon triggering by an event to achievepersonalization;

FIGS. 10 and 10A show the interaction of functional components of thepersonalization architecture and technical objects used during campaignmanagement;

FIG. 11 shows functional components of the personalization architectureportal interface with the user;

FIGS. 12, 12A and 12B show functional components and technical objectsof the personalization architecture relating to content management;

FIGS. 13 and 13A show functional components and technical objects of thepersonalization architecture relating to customer profile management;

FIG. 14 shows functional components of the personalization architecturerelating to user authentication:

FIGS. 15 and 15A show functional components and technical objects of thepersonalization architecture relating to management information systemreporting and customer analysis;

FIG. 16 shows how a decision on a value proposition to be offered to acustomer online is made by the system of the invention; and

FIG. 17 shows the Papaa model.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

With reference now to the drawings, FIG. 1 is an overall block diagramof the architecture of the invention for providing personalizedinteraction between a provider of information and/or goods and/orservices and a customer. A customer 1 interacts with the system throughany of a number of distribution channels 10 which may comprise, forexample, the Internet, automatic teller machines/kiosks, direct mail(email, fax, letter, etc.), Extranet, an Intranet, call centers, andbranch offices, without limitation. The system includes an integratedknowledge management component or personalization system 100 to bedescribed in greater detail. The component 100 implements such functionsas scoring (propensity rating), campaign management, knowledgeengineering, analysis and mining of information, data warehousing,forming customer profiles, providing customer profiles, and contactingmanagement. The system component 100 includes a decision engine to makedecisions to enable the system to personalize the interaction, apersonalization engine to personalize the interaction and a contentmanagement engine, amongst other components referenced later. The systemenables personalization of the interaction between the customer and aninformation/product/service provider offeringinformation/product/service 30 that the customer desires. For example,as shown by items 30, in the case of a financial institution, theproducts or services may comprise items such as home finance, smallbusiness credit, credit cards, automobile financing, savings deposits,other investments, insurance, education financing, etc. The systemincludes the necessary means to achieve product fulfillment. Althoughfinancial products 30 are shown in FIG. 1, the system is equallyapplicable to other information/services/products, such as goods orinformation. Integrated in the system are the necessary means forproviding security, authentication/recognition and authorizationdirectory services, middleware and workflow services, groupware such asweb/Intranet messaging and media services, network systemsinfrastructure and systems management services and support systems suchas compensation, fraud and compliance tracking systems, etc.

FIG. 1A is a linear technical architecture diagram showing the overalltechnical architecture of the system in the form of layers. It shows theinteraction from the distribution channels 10 on the left to the productlayer 30 on the right. For example, if a person interacts with thesystem via the Internet, the customer interaction session 12 is direct.The customer interacts through an authentication application 14 whichprovides work flow, entitlements, and allows beginning a session on thesystem. As the user crosses this layer, the user also registers thesession and retrieves any alerts/messages for the user. A presentationlayer 16 is then used to access the system. The presentation layer showsthe relationship—the total view—to the user. Infrastructure layer 18 isthe administration layer that allows the system to be maintained andadministrated. An application and business logic layer 20 includes thevarious applications and business logic, to be described in detailbelow. The layer 20 then interacts through an informationproduct/processor layer 25 with information/product/services 30 in theproduct layer.

Interacting with the various layers is a metadata-knowledgediscovery-object model 32 which includes various data bases andservices. These databases include a contacts database (db), work flowdb, security db, audit db, customer preference db, entitlement db,content db, application db, data warehouse db, data mart db, profile db,segmentation db, business rules db, campaign rule db and product db, inaddition to others.

Personalization is the ability to deliver targeted products, servicesand information tailored to the user's preferences, interests and needs.Personalization allows the creation of a customer experience whichreflects the relationship and the customer's requirements, also called“customer centric” experience. Furthermore, with respect to interactionvia an Internet web site, personalization allows filling “white space”which can be described as the ability to promote an interaction withmessages and other personalized components using matching and selectionbased upon the customer's profile, contacts, indications or assumptionsderived through analysis, past interactions or contacts and the currentinteraction. The system is designed to adapt to all touch points orchannels and all devices of interaction. Personal information can bestatic or dynamic based on a customer's explicit/implicit preferencesand historic data or dynamic based on real time assessment of the nextbest step.

Personalization is adaptable to all channels, as described above, suchchannels as the internet, extranet, phone lines, e-mail, automaticteller machines, branch offices, etc.

Personalization of the interaction between customers and providers ofinformation/goods/services is driven by a number of factors includingenvironmental factors and business goals. With respect to environmentalfactors, such factors as commoditization of a particular industry, thedisappearance of geographical boundaries, the dissolution of productidentities, consolidation and competition have caused a need todistinguish one's products and services from those of others and tobuild a system to obtain this distinction through personalization of theinteraction with the customer.

Business goals also drive the need for personalization. A customer feelsmore appreciated and more involved if there is personalized interaction.Further, personalization of the interaction empowers a customer andcreates an environment supportive of selling information/goods/servicesor cross-selling information/goods/services amongst differentdepartments of a provider of information/goods/services. Solutions aretailored due to knowledge of the customer.

The present invention provides a means to personalize an interaction viavarious communication channels between a customer and a provider ofinformation/goods/services. The present invention allows a customer tointeract with the provider through a preferred channel and at thecustomer's convenience. The system allows personalization of thatinteraction so that the customer is recognized and the customer's needsanticipated. The system allows advising the customer and providingaccess to all information/products/services offered by the provider.Further, the system allows the provider to provide customer tailoredpackages, i.e., non-standard packages. Furthermore, the system allowsfor continuously gathering, analyzing and distributing information tomake the customer receive a more rewarding experience and interactionwith the provider. Moreover, the system creates a basis for retainingcustomers, better servicing customers, and tailoring solutions as aresult of the personalization provided by the system.

According to the invention, once a customer contacts the providerthrough a communications channel using the personalized system of theinvention, the first step is identification and authentication of thecustomer at the start of the session (the security layer 14). Thistriggers the collection of a real time, customer profile which, createdand combined, provides the basis for the delivery of a personalizedexperience. The same functions and information are made available ateach touch point, i.e., through each channel. The actual experience thatthe customer has will be adapted to the customer's preferences and thecapabilities and environment at that touch point. A decision engineprovides key parameters for the real time assembly of the experience.Other parameters are the capabilities of the touch point and the courseof the dialogue, for example, the click stream if communication is overthe internet. The system is capable of interacting with the customerover a wide range of communication channels, however.

A Profile Manager, to be described in detail later, is the centralcoordinator and manager for all user profile related information. TheProfile Manager is designed to be a service broker with appropriatedirectory service and repository support and it mediates access to alluser profile related information. Sub-components of the profile managerprovide services such as authentication and authorization, aggregationof profile attributes including user preferences, segmentation andcampaign targeting/tracking information for the user, contactinformation, and outstanding commercial and services issues (“workflowprocess” status).

Value propositions i.e., offers to be made or information to bepresented to the customer, are matched with the customer profile needsand preferences and delivered at the right time and the right place.Each session will update the customer profile, trigger follow-upactivity and provide data for customer interaction analysis and finetuning of the customer dialogue and the value proposition (offer).

The steps in the personalization process include adaptation to thechannel, selection of functions, navigation screens and templates whichtake into account the specifics of the communication channel. The systemcustomizes the experience based upon predefined navigation, language andtone of voice, metaphor including color scheme graphics and layout. Newsand messages can be provided to the customer.

Further, the system personalizes the process by content selection, basedon preferences and customization rules. The system provides news andtopics to the customer using searching and filtering technologies.

Further, so called “white space” in the customer display can be filledwith propositions, actions, alerts, notifications, etc., decided byrules based on, for example, customer preferences or analysis of thecustomer profile.

In addition, the system can predict needs and can propose actions orrecommendations based on matching of user profiles and behavior of likeminded people. The system determines next steps based on analysis of thecurrent interaction, obtains feedback and learning to be captured in thecustomer knowledge base and includes a rule oriented data base forapplication of personalization to thereby personalize information,offers, terms, conditions, and financial advice, etc.

FIG. 1B shows an example of how the system operates. FIG. 1B shows oneexample of how the system personalizes in a cross channel environmentthe interaction with a customer. The customer in this particular case isa customer of a financial institution having a high average savingsbalance, for example, greater than $10,000.00, a credit card, and amortgage. The customer's characteristics are shown at 1A in FIG. 1C,along with the financial products, agreements and accounts 1B utilizedby the customer.

FIG. 1C shows an example of how the system would use various data forthis particular case study, i.e., the case study of FIG. 1B previouslyreferred to. The customer has various demographics, preferences, values,financial objectives and a lifestyle (1A). Further, the customer hasvarious agreements, if the service provider is, for example, a bank,such as credit cards and a mortgage (1B). Accordingly, the user makesuse of various products such as credit cards and a mortgage from theservice provider, in this case a bank. The user also may have accountswith the bank as shown. The system of the invention may also maintain aplurality of campaigns, contact lists, campaign responses, campaignpriorities, etc. (45). Campaigns may be, for example, programs currentlyoffered by the provider to customer prospects. The system furtherincorporates business/marketing rules and decision factors, targetindicators, etc. (47) for determining which campaign to target to aparticular user based on the rule/factors. This data model—called Papaafor applications in the banking industry—allows all personalization dataand actions to be modeled. This data framework allows for amulti-channel, multi-action system to be unified for mining and audit ofinformation. Papaa is an acronym standing for“Party-Agreement-Product-Account-Activity.” It is an object relationalframework. The object model defines the business logic and services toinsulate interfaces from the physical, relational database layer. Therelational model offers the flexibility needed to address and supportevolving entity attributes. Papaa is a framework defining the GlobalProfile Repository, discussed herein, for Personalization, supportingthe needs of the profile manager. The Papaa model is shown schematicallyin FIG. 17.

Referring again to FIG. 1B, a campaign manager 122, to be described indetail later, is programmed to run various campaigns (FIG. 1C), forexample, offering a credit card, currency on the go, home equity loans,a mutual fund and/or small business services. Based upon the customerprofile managed by profile manager 122, a personalization engine 112selects, for example, a mutual fund campaign to display on an ATM screen40 while the customer withdraws cash. The rationale for this decision isthe high average savings balance maintained by this customer. There is alikelihood that this customer will desire to invest in a mutual fund.Further, this decision may be based on other information available tothe system including lack of any knowledge of significant upcoming lifeevents, a comfortable lifestyle, and internal business/marketing rules.Should the customer be interested, the customer will express interest bytouching the ATM screen and ask to be provided with further details, forexample, by e-mail or any other means. E-mail can be sent with theinformation via e-mail server 121 and a link to a web page 50, and anelectronic form may be forwarded to the customer which can he used tocomplete the sale.

As FIG. 1B shows, alternatively, the customer may interact initiallywith the system by the Internet 45 in which case the mutual fund ad isdisplayed on a webpage 50. The customer then has the option ofcommunicating via the web site with the provider to consummate atransaction. Alternatively, another inbound and/or outboundcommunication channel(s) could be used, e.g., telephone, etc.

The personalization engine 112 is coupled to a decision engine 114making each personalization decision at an appropriate time, in thiscase, on the best campaign to present to the customer, also weighingwhich is the best option for the user. This is performed based onbusiness/marketing rules 47 (FIG. 1C) and the customer's profile. Aprofile manager 118 contains the profile of the customer which isretrieved and provided to the personalization engine 112 and which thepersonalization engine contact manager 120 updates based upon furtherinteractions. The campaign manager 122 is coupled to the personalizationengine 117 to provide any of selected campaigns for presentation to thecustomer. A contact manager 120 is also provided which is updated by thepersonalization engine 112 and records all the contacts with the usersof the system (user and provider). The CSR (customer servicerepresentative) is alerted by an event manager to call the customer toprovide further information or to close a sale.

With the above in mind, reference is now made to FIG. 2 which is anoverall block diagram of the system of the invention. The customerinteracts with the system via various channels 10, as previouslydescribed. The various products or services are shown at 30 aspreviously described. The personalization system (integrated knowledgemanagement system) is indicated generally by reference numeral 100. Asdescribed previously, to illustrate how the system operates in aparticular case, the system's primary components include interfaceidentification components 110 including a portal 111 for interfacingwith the channel 10 by which the customer interacts with thepersonalization system. The system 100 includes the personalizationmanager 112, previously described, for personalizing the interaction,the decision engine 114 which makes decisions concerningpersonalization, a content manager 116 which assembles and maps contentto be provided to the user by providing selected templates and screenobjects and a profile manager 118 which creates and caches the customerprofile based upon previous interactions and other informationconcerning the customer profile stored in a global profile repository118A. The system further includes a contact manager 120, campaignmanager 122, customer analysis component 124, alert/event manager 126,authentication component 128 and various information sources, internaland external, shown at 130.

With reference to FIG. 2, the portal 111 serves as an entry point andcommon connector that interconnects the various components. Componentsof the portal 111 include a repository which contains metadata aboutscreen objects, customer authentication/ACLs, preferences, profile,etc., a publish/subscribe engine, customer agents to deliver subscribedevents/messages, search engine-key word and boolean/crawler/filterengine, etc. Portals control and administer the user's complete “view”(what they see and how it is organized in each channel based on user'spreferences and entitlements etc.). Portal capability is essentiallycross channel. Portals provide the customer the capability to customizetheir view and tailor the view according to their preferences. Theytypically offer content folders to organize content into multiplelogical groups which may be shown in separate view zones, i.e.,transaction data, published information such as stock quotes, “whitespace” content driven by personalization and marketing, staticinformation, etc. User preferences can be channel specific (Internet hasa certain view while call centers should answer pre-configured view orqueries) and context specific (i.e., specific view while looking at, forexample, account balances).

The portal may use a single sign-on (SSO) server 198 (FIG. 3), to bedescribed later and the profile manager which collects the data forcustomer authentication and authorizations. The profile managermaintains a membership directory containing the information necessary toauthenticate and assign entitlement roles to each customer. It providesa single sign-on across all the web/application servers. It displays anindividual navigation menu with all the enterprise resources/servicesthe customer is authorized to access. The menu reflects the customer'sentitlements, and work flow which are obtained in real time based on thecustomer's current relationship with the information/product/serviceprovider.

The Profile Manager 118 manages all the details related to the user'sprofile. This component is essentially a service broker, which maps andmediates access to all user profile related information, which may bemaintained on multiple systems. These include user authentication andauthorization, profile attributes, user preferences, user-campaign taglists and related data, contact information etc. While all the above arenot accessed through the Profile Manager, it provides the data andservice directories to access this information as a service broker.

Some of the data elements related to a user's profile may be generatedby other systems directly, i.e., contact information or campaign taglists. However, the Profile Manager will provide reference maps andservices to access this information. Some other profile elements may beaccessed only through the profile manager, i.e., core profile elements.

The Profile Manager is considered the master reference for all userprofile related data. The Global Profile Repository (GPR) acts as thecentral directory or repository of all the data mappings, references,services. The actual data elements may physically be distributed indifferent databases (part of a common CRM data model).

The menus provided to the customer also reflect customer profiles,preferences and subscription services. Profiles and preferences aremanaged by the profile manager 118. The key functions of the profilemanager 118 include managing customer relationship events and assemblingcustomer profiles using an LDAP based customer directory which provideslinkages to all systems containing customer data and has supplementarycustomer information such as preferences, interests, etc.

If the internet is the chosen communication channel, as soon as thecustomer opens the home page, the portal 111 delivers personalizedassembled information relative to the customer's profile. This automaticassembly of content is done by the content manager 116. Thepersonalization is achieved via the personalization manager 112.

The content manager 116 aggregates content from multiple sources.Content sources may be of two categories, either static or dynamic.Static content may come from external feeds 130A, for example, weather,news, stock quotes, etc., and also from internal feeds 130B, forexample, product/service knowledge. Static content is served directly bythe portal 111 but stored/retrieved from the content manager 116.Dynamic and personalized content is served by the personalizationmanager 112, based on rules, work flow, interaction, campaigns andcollaborating filtering, amongst other techniques. The contentrepository 116A contains the actual screen content objects, for example,HTML files, images, and applets. FIG. 3 shows the system of FIG. 2 inmore detail.

The Portal 111 contacts the Content Manager 116 component for contentelements. The Content Manager manages the content components deliveredto the user. The Content manager may assemble content for channels whenthat is technically possible (i.e., Internet and e-mail) and willrequest content to be delivered in other channels where content isassembled by the channel specific application. However, content elementsrelated to personalization will be mapped into the content manager (mayor may not physically hold and assemble) and referenced by channeladapters which do their own content assembly and delivery.

For example. most of the content for channels like the Internet isstored in the Content Manager's repository 116A and assembled by theContent Manager, whereas contents of traditional ATM screens will bebased in the ATM driver or ATM itself, with personalized messages mappedand referenced from the content manager. The Content manager maps andassembles content from its own repository, business applications(transaction systems), other static and dynamic internal and externalsources, and resources referred by the Personalization Manager etc.Content elements for personalization will be decided by thePersonalization Manager 112 based on the provider's personalizationstrategy, as reflected by commercial rules, etc.

The customer analysis (data mining) component 124 utilizes the datamart125 to produce campaign rules, decision rules, and profile elements. Thecampaign manager 122 exports campaign rules to the personalizationmanager 112 and decision engine 114 and campaign content components tothe content manager 116. Campaign response tracking is used to provide areal time feed back loop on campaign effectiveness. Customer interestsand other campaign events are tracked in the content manager 116 forfollow-up.

The personalization manager is the hub of the system. It is a brokerwhich retrieves, weighs and sorts. The personalization manager 112 getsinteraction events, collaborative filtering results and customerprofile/preferences as input. It organizes and passes these inputs tothe decision engine 114. The decision engine 114 evaluates the inputsagainst its marketing/campaign intelligence rules stored therein to comeup with a decision or recommendation 114A. The decision is used by thepersonalization manager 112 to prepare value propositions (offers), bestnext steps and/or content to be presented to the customer. Thepersonalization manager 112 can also inquire of a collaborativefiltering engine, not shown in FIG. 2 or 3, but to be discussed indetail later, which makes decisions based on analysis of like mindedcustomers. Further, it can make decisions based upon an interactionanalyzer which analyses the current interaction, for example, clickstream analysis, to make a recommendation.

The Campaign Manager 122 generates and manages reports such as clickstream analysis, interaction analysis, customer analysis, campaignresponse analysis, etc. MIS Reporting—data marts—customer data martshold customer and transaction information and are accessed by customeranalysis components to assist campaign generation and targeting,segmentation, distilling of profile attributes, etc.

The Personalization Manager 112 component is a service coordinator andreceptacle that provides required services and data support forpersonalization. Essentially the personalization manager abstractsrequests for personalized content and helps manage otherfunctionality/services associated with personalization (such asdecisioning, campaigns, etc.). It accepts campaign rules from thecampaign manager and executes the rules in the context of the user withthe help of decision engines. This component can reference profilevariables through the profile manager (tag lists, attributes etc.),specific transaction values, event data, session data, etc. (madeavailable to decision engines as variables influencing a rule). It canalso accept, store and retrieve personalization and campaign relatedstatus in appropriate data repositories.

The Contact management 120 component aggregates and makes availablecross channel contact information across the product/service/informationprovider. All contacts, both inbound and outbound, generate informationabout the context of the contact (in what context the contact happened,i.e., customer wanted to withdraw money, had a service request, etc.).And the interaction that occurs during the contact (how the userinteracted, i.e., what was user's click stream or dialogue with theCSR). For example, the user may ask for all account balances, how muchmoney can be transferred at a time etc. before transferring money. Here,transferring money is the context, but the interaction includes all theactivities that happened during the interaction. The view of thecontacts made available at the different points will be based on theuser of the information (decided by business needs) and will be mediatedthrough contact manager services. The data may physically exist inmultiple systems.

The event manager 126 component provides a publish and subscribemechanism for events. An event is a stimulus that triggers an action.Events may result in a notification that can be delivered via multiplechannels. For example, the event that a check has bounced can generate anotification to a customer and/or CSR. (The process of notification isat times referred to as Alerts. However, for clarity and to avoidconfusion with the alert manager sub-component of the content manager,the term notification in this document issued to denote such alerts).The action could be executed by provider staff or by a provider businessapplication or a messaging/notification sub-component system.

Services of the channel/device identifier component 111A are used todetermined the channel through which the user has accessed the provideras well the capabilities and characteristics of the device (i.e.,browser type, security level, hand held device type, graphics support,type of ATM, link speeds etc.). The format and type of content(including functions permitted on this channel/device) presented will bebased on this identification. This component, nevertheless, does not doany modification to the content or participate in delivery of thecontent.

Turning now to FIGS. 4-7, these figures show the initial interaction ofa site visitor with a website personalized by the system of theinvention. For a first time site visitor 200, if anonymous and without aunique identification (201), the customer has an option to accept (203)or reject (204) an identifier. At this stage, personalization is basedonly on interaction based on current sessions, since there is no profileor history. Customization at this stage may relate to layout colors, andproduct/service offerings. Assuming the customer accepts the identifier(cookie), personalization can now be based on current and past sessionsand information passed by the cookie. When the customer gives explicitinformation (205) that the business provider wants, personalization isthen based on current and past interaction, collaborative filtering,rules using the customer profile and events. A determination (207) isthen made whether the customer is the customer that he claims to be byvarious authentication techniques, for example, social security number,account number, etc. Customization at this stage can include layout,colors, product information, news, weather, stock quotes, statements ofaccount, interest rate charges, etc.

FIGS. 5, 5A, and 6 show what the user sees and the data captured by theprofile manager global profile repository 118A (FIGS. 2 and 3) andinteraction data 118B which is captured by the system using thetechniques of personalization. The profile manager 118 creates a PIFentry (profile file) for the user, updates the PIF entry with explicitinformation and preferences, interests, etc., addresses, E-mailaddresses, phone numbers, demographic information like age, income groupor any other information that the information/service/product providerneeds and asks for any other demographic information, some of which canbe confidential such as social security number, relationships, etc. Thesteps in the dashed box, including steps 207-213, show some of theauthentication techniques.

FIG. 7 again shows the initial interaction between a site visitor andthe system, this time showing the personalization techniques used by thesystem at the various stages of the interaction. These include real timeclick stream analysis from current session interaction, click streamanalysis from previous sessions and collaborative filtering, to bedescribed in greater detail below, based on past interaction and datacollection. Further, personalization is based on other rules based oninteractions and explicit/implicit information. In addition, other rulesstored in the system in addition to those based on interactions anddemographics, e.g., include those based upon campaign transactions, thecustomer's profile and events including transactions and service relatedevents.

FIGS. 8 and 8A show a more detailed block diagram of the functionalcomponents of the system which are used in personalization. FIG. 8Ashows greater detail than FIG. 8. As described previously,personalization can be achieved through various techniques includingcollaborative filtering, interaction based on rules, including campaignrules and events. A value proposition database 114A, included in thedecision engine 114, has user specific value proposition informationlike the number of times the value proposition is shown, adjustedweightage for each value proposition, time stamps, the channel uponwhich the user is interacting with the system, etc.

With reference to FIGS. 8 and 8A, the content manager 116 passes arequest 116A from the user to the personalization manager 112 for arecommendation of a value proposition to be presented to the user. Aspart of this request, a user's profile is passed from the profilemanager 118 to the personalization manager 112. The user's interactiondata from the interaction data storage 130 is also passed as an input tothe personalization manager 112. These personalization manager queriesare passed to the decision engine 114 for application of rules. Thedecision engine 114 evaluates the various rules stored in the rules database 132. The decision engine 114 then passes back all the valuepropositions that the user should be targeted with based on a decisionprocess executed by the decision engine 114. Along with each valueproposition, the decision engine 114 passes a weightage and rule type.The personalization manager 112 will calculate the best valueproposition to present to the customer, as described below.

The personalization manager 112 then sends a request 133 tocollaborative filtering engine 134 for a recommendation. The filteringengine 134 uses various data elements including profile from profilemanager 118, interaction. etc. from the interaction data storage 130 toperform a “like mind” analysis. The collaborative filtering engine 134returns a recommendation 136, i.e., a value proposition.

The personalization manager 112 gets the weightage for this user for allthe value propositions obtained from the various sources including thedecision engine 114, collaborative filtering 134, etc.

The personalization manager 112 then balances weightages of variousvalue propositions and selects the best one for the particular user.

The personalization manager 112 updates, along with other flags, thevalue proposition data base 114A to adjust the weightage for thisparticular user and this particular value proposition and records theuse of the proposition in the campaign manager. The personalizationmanager 112 then contacts the product configurator 136 which builds apersonalized proposal depending on the user's profile andproduct/service (value proposition) profile 136A.

If the value proposition has been selected by the decision engine 114and the rule type satisfied for the value proposition is a campaign,then the decision engine 114 checks the corresponding campaign, categoryfor this user. The selected value proposition need not be a campaign, itcould be an alert, etc. If the user is present, the decision engine 114updates flags in a tagged list 138. If the user is not present then itadds the user to the list 138. The personalization manager 112 thensends the best value proposition to the content manager 116 whichprovides the selected value proposition to the user and assembles thecontent thereof via the portal 111 and selected channel 120.

FIGS. 9 and 9A shows functional components for event triggeredpersonalization; FIG. 9A in greater detail. An event is a stimulus whichtriggers an action. The action could be executed by theinformation/service/product provider or by a business application. Abusiness application can publish events whenever any business action isexecuted. External feeds can trigger events. The following types ofevents can be distinguished although they are not exhaustive: lifeevents, market/bank information, feed events, customer relationshipevents, sales related events, advice related events, service relatedevents, transactional/work flow events, user session events, profilerelated events, etc.

The campaign manager 122 generates target customer lists 140. Events 142can be associated with campaigns. These events are subscribed with thealert/event manager 126. The campaign manager also sets frequency ratesfor the campaign against the tagged list as well as tracks cost dataregarding the campaign.

The flow for event triggered personalization is as follows. Businessapplications 141 trigger various types of events. All generated eventsare associated with a particular user (customer/prospect). Thealert/event manager 126 subscribes to all events for all customers,implicit or explicitly by the user.

The alert/event manager 126 publishes the event to all the subscribersof the event. One of the subscribers is the personalization manager 112.The alert/event manager 126 passes this event to the personalizationmanager 112 through a queue 144. The personalization manager 112 picksup this event from the queue 144. The personalization manager 112 checksthe user associated with the event. The personalization manager 112retrieves the user's profile from the profile manager 118. The contentmanager paints and pushes the event information to the subscriber.

Using the decision engine 114, the personalization manager 112 selectsthe most appropriate value proposition at that time for the event andfor the particular user. The notification service 146 gets the user'spreferences from the profile manager 118 to find out the user'spreferred outbound contact channel, which may be one of the inboundchannels 10 or different outbound channels. The notification service 146gets the content (or pointer to content depending on the channel) forthe value proposition to be delivered on the selected channel from thecontent manager 116. If the value proposition is to be delivered on aninbound access channel 10, then the value proposition is saved in theuser's profile in the profile manager 118. This can be used for laterdelivery on the channel, for example, the Internet, when the user comesback to the provider. The notification service 146 updates the profilemanager 118 with the outbound activity 150. For outbound delivery 152,the notification service 146 creates a contact/activity list insales/service application 154 and informs the outbound delivery service156 to deliver. The outbound delivery service 156 actually initiates thecontact across various channels 158, for example e-mail, paper mail,faxes, etc. The sales/service application 154 is updated by the outbounddelivery service 156 with the status of the outbound contact/delivery.

FIGS. 10 and 10A show functional components related to campaignmanagement. FIG. 10A shows greater technical detail.

Customer analysis (data mining) 160 utilizes the data warehouse 162 toproduce campaign rules including propensity rating (scores) for aparticular customer. Marketing personnel 164 initiate campaigns forproduct promotion. The campaign manager 122 accepts the product/valueproposition input and registers campaign related content components withthe content manager 116.

Campaign targeting 122A validates the generated campaign rules 166. Itgenerates a tagged customer list 168 with the help of the profilemanager 118. Campaign targeting 122A exports the campaign rules 166 tothe personalization manager 112 and, in particular, to the decisionengine 114. Campaign targeting 122A also creates a contact and activitylist 168 in sales applications 154 and informs the outbound deliveryservice 156 to start the outbound contact activity across variouschannels, for example, E-mail, paper mail, telephone calls, faxes, etc.The campaign is then executed on the chosen outbound channels 158.

Customer/prospect responses 170 can be of two types. One is that thecustomer seeks more information about the campaign or product. Thecontact response information is captured in real time and passed tocampaign tracking 122B. The response is also fed to the sales/serviceapplication 154. This assists in scheduling further follow-up or canalso be for no further outbound contact in the case of a negativeresponse. Other kinds of response includes that the user/prospectactually buys the targeted product, e.g., by opening an account 171.This is entered in the fulfillment application 172. The fulfillmentapplication 172 generates a fulfillment response 174 keyed to campaigntracking 122B. Fulfillment response is also recorded in sales andservice applications 154 to follow-up.

Campaign tracking 122B updates the tagged targeted list 168 with theresponse. This helps the personalization manager 112 to take appropriatenext action on inbound contact with the user from channels 10. Responseanalysis 176 analyzes the campaign response using a decision engine 178.This information is passed back to marketing 164 which can evaluatecampaign effectiveness. The feedback is looped back into the existingcampaigns and/or used for future campaigns.

When a customer/prospect interacts on an inbound channel, thepersonalization manager 112 evaluates the campaign rules 166. If thecustomer satisfies the campaign rules and is not present on the list,then the user is added to the list with relevant information. Thepersonalization manager 112 then provides the campaign value propositionto the user via the content manager/assembler 116 and portal 111. If theuser is already on the list then the personalization manager 112 alsooffers the value proposition to the user.

FIG. 11 shows the functional components of the portal and contentassembler.

The content folders 190 are a set of business defined logical groups ofone or more topics. The business provider can publish information to thefolders and users can subscribe to them. Preferably, the folders do nothave the actual content. Instead, they have pointers to content. Theactual content preferably resides in the content repository 192connected to content manager 116. A folder 190 may have restrictions foraccess as specified by the business provider.

A metadata repository 194 is also provided. The metadata repositorycontains pointers to the content elements, user preferences, contentfolders, ACLs, etc. This is information on how to reach a particularitem of information.

The customer agents 196 work in the background to automatically searchcustomer defined events and to save the content in the customer specificcontent folder 190. They also pre-fetch commonly requested informationin the same folder.

The flow of content between user and portal 111 and the personalizationmanager 112 is as follows:

After the user is identified or authenticated by SSO 198, the request ispassed to a channel access manager 111A. The channel access manager 111Aidentifies the user's channel and device that the user is using andpasses the user identification and device/channel characteristics to theportal 111. The portal 111 fetches the user's preferences from theprofile manager 118. Based on the user's channel characteristics andpreferences, the portal 111 selects an appropriate template from themetadata repository 194. Based on the user's subscription stored in theprofile, the portal gets the general content folder information andcustomer specific folder information from the metadata repository 194based on pointers in folders 190. The content folder information ispassed to the content manager 116.

The content manager 116 then returns a filled personalized content 200.This content, personalized to the customer, is delivered to the userthrough a delivery engine, not shown.

Offline, a crawler filter engine 202 automatically scans specified datasources for objects of interest. It classifies them and places theactual content in the content manager 116 and appropriate information ina content folder 190. This occurs off line. Additionally, also offline,a search engine 204 enables users to find objects using key words likenames, descriptions, content types and filters. The user could be alertor notified upon return of new content.

FIGS. 12 and 12A show functional components for content management.

Content can come from two types of content sources, either a dynamiccontent source 161 or a static content source 163. Dynamic content isprovided by applications like the personalization manager 112. Campaignrelated content is also selected dynamically and registered with thecontent server. Static content 163 can come from external feeds 201, forexample, weather, news, stock quotes or internal feeds 203, for exampleproduct knowledge.

The content repository 116A contains content elements, pieces ofcontent, for example, HTML files, images, applets, for selectedchannels, for example, the internet, web, ATM, etc. and pointers tocontent for other channels, for example, IVR, Siebel, etc. It also hasinformation to map a value proposition to the content manager 116.

The flow for content management is as follows:

The portal 111 passes (181) a template name to the content manager 116.It uses the layout manager 208 to retrieve the actual template from thecontent repository 116A. The template is passed to the content assembler210 which evaluates the template. It is divided into zones and each zonehas a pointer to the source of the content. One or more zones can pointto the personalization manager 112. The content assembler queries thepersonalization manager 112 for a value proposition. The personalizationmanager 112, using various techniques including the decision engine 114and personalization rules database 114A, returns the best valueproposition to the content assembler 210. The content assembler 210 mapsthe value proposition to the actual content element which is selectedfrom the content repository 116A. The content assembler 210 returns theassembled content to the portal 111 for passage to the user.

Off-line, a version manager 212 publishes a notification event whenevera specified content element is changed. The portal 111 subscribes tothis event and puts it in the user's content folder 190. The versionmanager 212 also notifies the owner of the content for version update.The content mapper 214 offers the content designer 216 amulti-dimensional view of the content element. It shows all othercontent that refers to this content, all channels that it is used in,all rules that point to this content, etc. The content mapper 214provides content integrity and cross references. All content isadded/removed/administered through the content mapper 214.

FIGS. 13 and 13A show functional components for profile management. Theprofile manager 118 is a broker which offers pointers/linkages tosystems containing customer/prospect data. It contains supplementaryinformation such as customer preferences. It assembles customer profilesusing the global profile repository 118A. The profile manager ispreferably integrated with single sign on (SSO) 198. It holdspsychographic, demographic and other data elements related to a profile.

Online identity and credit verification of new customers can be by knownmeans of online inquiry or external systems such as Bureauflex. Theprofile manager 118 is the gateway to any customer related information.It provides an aggregated view of the customer information. It providesa common API/messaging interface to all other business/providerapplications. The profile manager 118 shields everyone from collectingdistributed data across the business/provider.

Over a period of time, as the available customer data increases, theprofile can be enriched to update the psychographic variables throughknowledge discovery 220. The profile is enriched with the knowledgederived from various applications like the campaign manager 122, MISreporting 160, collaborative filtering 134 and other interactionscollectively indicated at 190.

FIG. 13A shows the architecture of the profile manager 118 in greaterdetail.

FIG. 14 shows functional components relating to single sign on (SSO).

All user authentication requests are passed to an authentication andauthorization server (AAS) 230. The AAS 230 maintains/manages a securityregistry 232 which holds all customer/non-customer security identifierslike user name, password, access control layer, roles, etc. Whenever anew user signs up, the AAS 230 creates the same user scheme for acustomer and/or prospect in the profile manager 118.

The flow for single sign on is as follows:

On any user request, the identification component 234 identifies if theuser's request needs authentication. If the request is for anon-restricted item, the request is passed forward and the profilemanager retrieves the user's preferences and alerts the content managerto assemble the view to the portal 111. If the request is for restricteditems, it is passed through the AAS 230. The AAS 230 authenticates theuser by verifying the user's identification/password. This is done bychecking against the security registry 232. If the user isauthenticated, along with the authentication status, the AAS 230 returnsa navigation menu to the identification component 234 which holds thecustomer's entitlements for application servers and services. This isbuilt by the AAS 230 based on rules. The AAS 230 also returns encryptedauthentication tokens to the identification component. The token holdsthe user name, roles and validity information. The authentication tokenis stored in the customer's session. The token is passed with everysubsequent service request to the corresponding web/application server,as shown at 233.

The access token is passed with every subsequent service request fromthe user. The token verification layer 234A verifies the tokens. If thetoken passes the verification process, the service request is passedforward, as shown at 236. Otherwise, it is blocked and the user isdenied access to the service.

FIGS. 15 and 15A show functional components related to MIS (managementinformation systems) reporting.

Data mining is the extraction analysis of data for purposes ofdiscovering knowledge for large data bases. Data mining tools automateprediction of trends/behaviors and discovery of previously unknownpatterns, allowing businesses to make proactive, knowledge drivendecisions and new business logic/rules. Data mining can be performed onany user related data available across the information/product/serviceprovider. Analysts 240 can extract a snap shot of the data bases 400 andrun data mining tools in a separate analytical environment.

An analyst 240 using the customer/prospect data in the profile manager118 and data mining tools can create a predictive propensity model. Fromthis model, the data mining tools generate a customer segment, rules andpropensity score for a customer segment. This can operate also inreverse. Marketing can define a customer segment by a rule in thecampaign management application and data mining can generate apropensity model and score the customer segment in the campaignmanagement application.

Campaign response data 250 can be fed to data mining applications 160 toanalyze the response data. The response can be used to modify existingcampaigns or for future campaigns. It can also derive certaincustomer/prospect attributes which can be updated through the profilemanager 118.

User interaction, for example, click stream on the internet, can becaptured and analyzed in real time, as shown at 260. Analysis can derivecontext out of the interaction. The context can generate interactionevents, which can be sent to the alert/event manager 126. These eventscan be further sent to the personalization manager 112 for selecting thebest value proposition. Interaction analysis 260 can generate newpersonalization rules based in real time for the personalization rulesdatabase 132. Interaction analysis 260 can also derive customer behaviorpatterns, channel usage, navigation patterns etc.

A contact manager 120 (see FIG. 2) captures contracts made with thesystem and stores these in contacts data base 270. Contacts can beanalyzed using contacts data mining tools 162 to understand the usercontact patterns, channel usage and purpose, etc. This can be fed backinto the user's profile. Contacts can be used for purposes of audit,security, service analysis, and business processes.

As described, the present invention provides the ability forcross-channel applications to offer services, functions, andcapabilities across all channels and allows the user of the system tohave the ability to create a customer centric experience as well asallowing data knowledge to be gathered, analyzed and used. Across-channel application can be used on any channel, for example,internet, ATM, phone lines, call centers, etc. Cross-channelapplications can be layered on top of industry standard technologyinfrastructure, for example, message oriented middleware, componentbased architecture, industry standard platforms such as EJB, JMS, XML,MQ series, LDAP, BEA Weblogic, Oracle DB, Java Script scripting Engine,Sun Solaris and Unix, without limitation. Cross-channel applicationservices are available to the different types of applications includingthe profile manager 118, the personalization manager 112, the eventmanager 126, the product configurator 136 and other cross-channelapplications. All cross-channel applications can be made available onboth external messaging and an internal EJB bus. To ensure performanceand scalability, cross-channel applications are preferably hosted on anEJB application server environment. To meet today's fast changingbusiness environment. a scripting capability can be provided to link thebusiness service components to shorten the cycle time for rolling outnew/updated business services.

FIG. 16 shows in greater detail how the personalization manager 112calculates the best value proposition or offer to a customer on line.

A rules value proposition list 300 contains a list of all best valuepropositions with rules for each value proposition. This list isspecific to a user. For a value proposition which is waiting for adelivery to a customer, the value proposition list is provided by thedecision engine 114 and collaborative filtering 134. These are saved inthe value proposition list 300.

A user proposition history object 302 contains the value proposition andthe weight of each for a user. This information is extracted from aproposition history data base 304. The weight of the value propositionbeing offered to the user is reduced further. On session termination,all this updated information is written back to the proposition historydata base 304.

The proposition history access object 302 accesses the propositionhistory data base 304 to get/set a value proposition weight list for auser. In case of an off line request, the found best value propositionis stored in the proposition history database 304.

The value proposition object 302 contains the best proposal that can beoffered to a user. It contains the value proposition related rule andproposal information.

The flow for calculating the best value proposition is as follows:

First, a request to find a best value proposition for a user is passedto the calculate best value proposition component 306. The calculatebest value proposition component 306 determines whether it is necessaryto present any personalized proposals to the user. This is based uponthe personalization rules data base 132 and rules evaluator 132A that ispart of decision engine 114. The rules are applied on the request forthe particular user and session. A user profile is then obtained fromthe session manager 308. This is used as one of the inputs to derivevalue propositions. The user profile and session information are keptready for use by the decision engine 114. The decision engine 114 isused to extract a value proposition list for the user. The calculatebest value proposition component 306 also finds out whether any valuepropositions are waiting for delivery for this particular user. Any suchvalue propositions are stored in the user proposition history object302.

The decision engine 114 and collaborative filtering engine 134 are thenqueried to derive value proposition lists best suited for this user. Thedecision engine 114 applies rules on the user and session information ithas and derives a value proposition list 300. Collaborative filtering134 gives a list of value proposition/recommendations after performing a“like mind analysis.” The returned lists are stored in the Valueproposition list 300.

The calculate best value proposition component 306 balances weightagesof various value propositions and selects the best one for this userfrom the complete list present in the rules/value proposition list 300.The product configurator 136 keeps a mapping of all value propositionsto proposals that can be offered to a particular user. It applies rulesand finds out whether the proposal for a value proposition can beoffered to the user. In case a value proposition cannot be offered to auser, the calculate best value proposition component 306 checks for thenext best value proposition.

If the chosen value proposition is a result of a campaign, then the useris added to the tag list 310 if the user is not already present. If thecampaign has expired, then the value proposition/rules are deleted andthe next value proposition is checked with the product configurator 136.The best found proposal is stored with its rules in the best valueproposition object 312. In case of an on line request, this proposal isreturned to the user. If the request or user is off line, it is saved inthe proposition history data base 304 for later on line use.

Personalization is a process by which the system of the inventionidentifies the best value proposition to be delivered to the user. Thiscan be done in several ways. One way is to calculate the best valueproposition in real time on every click and show it to the user. Anotherway is to calculate/save a list of value propositions off line, evenwhen the user has not come to the service provider. This means that theservice provider does not use the user's context and current sessionclick stream as inputs. Further, this would not use the contact historythat the user may have generated after the off line activity. Anotherway is to calculate/save a list of value propositions at the start ofthe session and at every click select one and show it to the user.Again, this method does not use the user context and current sessionclick stream.

Another option is to categorize rules as session static and sessiondynamic and at the start of the session or when off line calculate andsave a list of value propositions. Later, when on-line, on every clickthe session dynamic rules can be evaluated. The downside to this methodis that new session static rules that are added during the sessioncannot be utilized. The choice between the various options is acompromise between being effective and performance.

With reference again to FIG. 8A, the decision engine 114 manages a rulevariable dictionary 114B. The rule variable dictionary 114B is a datastructure which holds information of all the attributes shown. It is alist of variables and associated information that can be used forpersonalization. The rule variable dictionary includes the followingcategories of variables: profile attributes from the profile manager,session attributes from the session manager, context variables from thecontent manager, and events from the event manager. See FIG. 8A.

The rule variable dictionary 114B is updated to match the correspondingdata model or attribute list of each of the above systems. In order toset up the dictionary, all the attributes are entered in the dictionary.The attributes can be entered either manually in the dictionary via auser interface 115 or can be updated by a programming interface 115A.

The personalization manager 112 preferably has a graphical userinterface (GUI) through which marketing personnel can refresh thedictionary whenever required. This could also be done in real timewhereby each of these systems could update the personalization manager112.

The collaborative filtering engine 134 returns recommendations basedupon user input and is fed with the user list 135 along withpsychographic data and the value proposition list 137. The collaborativefiltering engine 134 uses ratings which customers provide with respectto value propositions, i.e., information/products/services offered.Based upon these ratings it can then determine what types ofinformation/services/products should be offered to the user. Another wayto do this is over a period of time. After customers use the system,ratings can be defined based upon the user's preferences. Based uponthese preferences, the collaborative filtering engine 134 can makerecommendations as to other information/products/services.

Turning again to the content manager (FIG. 12A), the content manager 116maintains a content dictionary 116B which is maintained in the contentrepository 116A. The content repository 116A is organized in the form ofa tree structure termed a “content dictionary” 116B. The contentdictionary is a hierarchical tree of content category by which contentelements are classified. The tree structure allows content to be groupedinto categories and further subcategories. The root of the contentdictionary tree is called “NCS root”.

The first three branches from the root are as follows: The first branchis the layout category subtree. All template/layouts are stored underthis node. They are further classified as branches. Each such branchrepresents a unique template which can be directly mapped to userpreferences. They are not further branched. The second branch is thefunction category subtree. All functions are stored under this node.They are further classified as branches and sub-branches. Each has aunique function which can be directly mapped to user preferences.

The third branch is the data category subtree. All data categories arestored under this node. They are further classified as branches andsub-branches. Each sub-branch represents a unique data category whichcan be directly mapped to user preferences.

Still referring to FIG. 12A, and with further reference to FIG. 12B, thecontent assembler flow is as follows: Every incoming request (URL)directly refers to a layout category. Each layout category may have anumber of layouts. The correct layout is chosen based on the user'slayout preference and on the device and channel the user is utilizing.Each layout has an associated template which defines visualcharacteristics. This template defines multiple zones and a functioncategory for each zone. Each function category has one or morefunctions. Appropriate functions are chosen based on the user'sinterests amongst all the functions in this function category stored aspreferences with the profile manager. A function contains a template andone or more data categories. This function template provides aconsistent way (for a device/channel) in which the function is displayedirrespective of the data category. A data category is a node in thecontent dictionary 116B. Each function may have one or more datacategories and also have one or more data elements. For all staticcontents, appropriate data elements are chosen based on which dataelement the user is interested in amongst all the data elements in thisdata category. This interest is stored as a preference with the profilemanager 118. For all dynamic content a separate adapter component can bewritten. This component can communicate with an application and get backthe data elements.

Content is gathered for personalization as follows: Personalization is afunction category specified in a zone. A content selector contacts thepersonalization manager to resolve this function category to a valueproposition for the customer. The value proposition is mapped to afunction for the channel and device. The function has a template and oneor more data categories and is processed accordingly as other functions.

Transactions, for example, a balance summary, transfers, etc. are afunction by themselves. Transactions contains a template and a datacategory. The transaction data category has a corresponding objectcomponent to be called and provides the data for the transaction resultto be displayed.

The product configuration is the data category with a correspondingobject component to be called and provides the product configurationinformation for a given product for the customer in session. Forexample, if a home equity loan is being proposed, the productconfiguration will provide terms and conditions for this customer basedon the customer's relationship and credit information.

Events, pending for delivery during inbound customer interaction, belongto a specialized event data category. The corresponding object componentwill be called to retrieve the pending events for customer display.

Turning again to the event manager (FIG. 9A), all events are stored inan event tree 126A. The tree structure allows event types to be groupedinto categories and further subcategories. Each branch in the treerepresents a subcategory of the event it branches from. The event treeis built dynamically. When a new event type is added to the environment,it is added to the tree so that it is available for subscription. Accessto the event tree can be either to read or to write. A write access addsan event type to the tree. The tree is read to publish the event to allthe subscribers.

The event properties describe the event itself and further relevantinformation associated with the event. Event agents 127 generate eventsthat are in the event tree. For the first event. a new event type iscreated in the tree. This is done by calling one of the operationsoffered by the event manager. Every time, including the first time, theevent agents 127 generate the event and pass event properties to theevent manager 126. Subscribers subscribe to events that are in the eventtree. For the first time they subscribe to the event and every timeincluding the first time they receive the event along with eventproperties.

Event subscriptions are customer applications which subscribe to eventsor event categories. They can specify the following subscriptioninformation: Extra conditions that must be satisfied before the event isforwarded to them. The event manager 126 will evaluate these conditionsbefore forwarding the event. They also specify what action to performwhen the event occurs. They also indicate the expiration of thesubscription. The conditions are evaluated and the action is performedby the event manager 126. The client application specifies this in aform of class name. These classes are installed on the event manager.

Event agents 127 are applications that generate events. They monitorrequired data sources. Event agents have user preferences about theevent that they can generate. A new event that is sent to the eventmanager 126 will have a user ID associated with it. Event agentscommunicate with the event manager 126 through standard adapters 129which support, for example, XML over MQ series, EJB interfaces, etc.Custom adapters can be built to support additional interfaces, forexample, news agents, stock agents, transaction agents.

The LDAP comprises the following: A profile data dictionary, interfacedictionary and a storage dictionary. The profile data dictionary is adictionary to hold the data model of the profile. The data model isstored as a hierarchical tree. It has a list of profile attributes. Thetree is stored in an LDAP directory. The profile dictionary managerautomatically updates the interface and storage dictionary whenever theprofile data dictionary is modified.

The interface dictionary holds information about the source of theattributes. It describes how each attribute needs to be fetched andwhich adapter to use. It describes that the attributes have to befetched in real time or in batch mode, the frequency, age, etc.

The storage dictionary holds an internal storage and retrieval relatedinformation like the table name, field name, name, etc. this dictionarydescribes each and every attribute and attribute category. Theseattributes are saved in multiple tables across data bases. Thisdictionary is stored in an LDAP directory.

The profile data base physically holds the actual profile attributes.Storage of the attributes is optimized for retrieval/update of theattributes and may not be the same as the profile data model.

Returning to FIG. 13A, the data access manager 118B manages all read andwrite access to the customer profile database. It aggregates scatteredattributes from internal and external storage systems. For reading theprofile, it reads the storage dictionary 118C. This gives informationabout how to fetch the profile. Various methods can be used to fetch theprofile, for example, obtaining it in real time from the source systemthrough the interface manager 118D, reading from the local database,etc. For each method, there is additional information which aids infetching the profile. In writing the profile, the data access manager118B uses the storage dictionary 118C. The dictionary tells where towrite the profile attributes.

The interface manager 118D manages interfacing to business systems.Anything coming in or going out occurs through the interface manager118D. It uses suitable interface adapters 118E to gather/exchangeprofile information.

The global profile repository 118A is built by pushing and pulling.Certain attributes are fetched in real time when required. Certainattributes are downloaded periodically, for example, in batch mode.Applications can update the profile attributes in real time. Certainattributes can be written in batch mode. The profile attributes can haveACLs for read/write access. Any read/write access to the global profilerepository 118A preferably should be through an authorization component.The data access manager 118B can impose these restrictions.

Although the present invention has been described in relation toparticular embodiments thereof, many other variations and modificationsand other uses will become apparent to those skilled in the art.Therefore, the present invention should be limited not by the specificdisclosure herein, but only by the appended claims.

What is claimed is:
 1. A computer-implemented method for personalizinginteraction between users and a provider in a multi-channel accesssystem for accessing information of a plurality of products, comprising:storing in at least one non-transitory computer memory, data andinstructions pertaining to users including account information;accessing the at least one computer memory using a computer processor ata central server system to execute instructions and to perform stepsincluding: storing data in said at least one computer memory includingaccount information for existing accountholders for at least onefinancial product; transmitting, by the central server system,information electronically to at least some of said accountholders withsolicitations to become registered accountholders for receivingpersonalized value propositions; registering accountholders at saidcentral server system based on positive responses to solicitations tobecome registered accountholders for receiving personalized valuepropositions; storing in said at least one computer memory informationof the registered accountholders; receiving financial transactionrequests from accountholders electronically at said central serversystem; determining whether an accountholder making a request is aregistered accountholder by comparing to information of the registeredaccountholders; processing a plurality of value propositions at saidserver system to determine candidate value propositions for therequesting accountholder after determining that the accountholder is aregistered accountholder; selecting, by said central server system, fromsaid candidate value propositions at least one personalized valueproposition for the requesting accountholder; electronically issuing theat least one personalized value proposition to said accountholder.
 2. Acomputer-implemented method for personalizing interaction according toclaim 1, further comprising issuing a plurality of personalized valuepropositions for different financial products.
 3. A computer-implementedmethod for personalizing interaction according to claim 1, furthercomprising issuing a plurality of value propositions including at leastone value proposition corresponding to an existing account provider andat least one value proposition corresponding to a third party other thansaid existing account provider.
 4. A computer-implemented method forpersonalizing interaction according to claim 2, wherein the differentfinancial products corresponding to the value propositions include acredit card account and at least one other product.
 5. Acomputer-implemented method for personalizing interaction according toclaim 1, further comprising: performing fulfillment of a personalizedvalue proposition upon acceptance by the requesting accountholder.
 6. Acomputer-implemented method for personalizing interaction according toclaim 1, wherein the request made by an accountholder is a credit cardtransaction.
 7. A computer-implemented method for personalizinginteraction according to claim 1, further comprising transmitting saidat least one personalized value proposition in a home page personalizedfor said accountholder based on profile data.
 8. A computer-implementedmethod for personalizing interaction according to claim 1, wherein theat least one personalized value proposition comprises one or more ofcurrency and a new financial product.
 9. A computer-implemented methodfor personalizing interaction according to claim 1, wherein theplurality of candidate value propositions are for a plurality ofdifferent financial products.
 10. A computer-implemented method forpersonalizing interaction according to claim 1, wherein each of thecandidate value propositions is assigned a weight or score based on therequesting accountholder.
 11. A computer-implemented method forpersonalizing interaction according to claim 10, further comprisingadjusting down the weight or score of a candidate value propositionbased on determining that the value proposition was previously issued tothe requesting accountholder.
 12. A computer-based system forpersonalizing interaction between users and a provider in amulti-channel access system for accessing information of a plurality ofproducts, comprising: at least one processor at a central server system;at least one non-transitory computer memory coupled to the processor,the computer memory storing account information for existingaccountholders for at least one financial product; a content engine atsaid central server system transmitting information electronically to atleast some of said accountholders with solicitations to becomeregistered accountholders for receiving personalized value propositions;a profile engine at said central server system registeringaccountholders based on positive responses to solicitations to becomeregistered accountholders for receiving personalized value propositions;a profile database in said at least one computer memory storinginformation of the registered accountholders; a channel serverelectronically receiving financial transaction requests fromaccountholders; wherein the central server system determines whether anaccountholder making a request is a registered accountholder bycomparing to information of the registered accountholders; apersonalization engine processing a plurality of value propositions atsaid server system to determine candidate value propositions for therequesting accountholder that is a registered accountholder; wherein thepersonalization engine selects from said candidate value propositions atleast one personalized value proposition for the requestingaccountholder; and wherein the channel server electronically issues theat least one personalized value proposition to said accountholder.